Submitted:
27 July 2026
Posted:
29 July 2026
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Materials and Methods
2.1. Sample Sources
2.2. Sample Analyses
3. Databases
4. Database Analysis and Statistics
5. Results




- 11.Not listed are patients with balanced translocations (11), marker chromosomes (4), pericentric inversions (2), or triploidy (10). Only the 54 microdeletions/duplications found in 3 or more patients are listed, recognized microdeletion/duplication syndromes in larger type and bolded; aCGH, array-comparative genomic hybridization or microarray analysis; CduC, cri-du-chat; DG, DiGeorge; Dx, diagnosis; PW/A, Prader-Willi/Angelman; SM, Smith-Magenis; Sx or S, syndrome; Transloc., translocation; W, Williams; WH, Wolf-Hirschhorn.

Discussion
Supplementary Materials
Author Contributions (by CRediT categories)
Acknowledgments
Conflicts of Interest
Data and Code Availability
Statement
Ethics declaration
References
- Nurk, S.; Koren, S.; Rhie, A.; et al. The complete sequence of a human genome. Science 2022, 376, 44–53. [Google Scholar] [CrossRef]
- Olson, N.D.; Wagner, J.; Dwarshuis, N.; et al. Variant calling and benchmarking in an era of complete human genome sequences. Nat. Rev. Genet 2023, 24, 464–483. [Google Scholar] [CrossRef] [PubMed]
- Beaudet, A. The utility of chromosomal microarray analysis in developmental and behavioral pediatrics. Child Dev. 2013, 84, 121–132. [Google Scholar] [CrossRef] [PubMed]
- Coulter, M.E.; Miller, D.T.; Harris, D.J.; et al. Chromosomal microarray testing influences medical management. Genet Med. 2011, 13, 770–776. [Google Scholar] [CrossRef] [PubMed]
- Yuan, H.; Shangguan, S.; Li, Z.; et al. CNV profiles of Chinese pediatric patients with developmental disorders. Genet Med. 2021, 23, 669–678. [Google Scholar] [CrossRef] [PubMed]
- Mardy, A.H.; Wiita, A.P.; Wayman, B.V.; Drexler, K.; Sparks, T.N.; Norton, M.E. Variants of uncertain significance in prenatal microarrays: a retrospective cohort study. BJOG 2021, 128, 431–438. [Google Scholar] [CrossRef] [PubMed]
- Tao, Y.; Guo, H.; Han, D.; et al. Uncovering genetic contributors to developmental delay and intellectual disability: a focus on CNVs in pediatric patients. Front Genet 2025, 16, 1539902. [Google Scholar] [CrossRef] [PubMed]
- Pande, S.; Dawood, M.; Grochowski, C.M. Structural variants: Mechanisms; mapping; and interpretation in human genetics. Genes 2025, 16, 905. [Google Scholar] [CrossRef] [PubMed]
- Betancur, C. Etiological heterogeneity in autism spectrum disorders: More than 100 genetic and genomic disorders and still counting. Brain Res. 2011, 1380, 42–77. [Google Scholar] [CrossRef] [PubMed]
- Ceylan, A.C.; Citli, S.; Erdem, H.B.; Sahin, I.; Acar Arslan, E.; Erdogan, M. Importance and usage of chromosomal microarray analysis in diagnosing intellectual disability; global developmental delay; and autism; and discovering new loci for these disorders. Mol. Cytogenet 2018, 11, 54. [Google Scholar] [CrossRef] [PubMed]
- Miller, D.T.; Adam, M.P.; Aradhya, S.; et al. Consensus statement: Chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. Am. J. Hum. Genet 2010, 86, 749–764. [Google Scholar] [CrossRef] [PubMed]
- Kaminsky, E.B.; Kaul, V.; Paschall, J.; et al. An evidence-based approach to establish the functional and clinical significance of copy number variants in intellectual and developmental disabilities. Genet Med. 2011, 13, 777–784. [Google Scholar] [CrossRef] [PubMed]
- Wyandt, H. E.; Wilson, G.N.; Tonk, V.S. Chromosome Structure and Variation: Heteromorphism; Polymorphism; and Pathogenesis; Springer, 2017. [Google Scholar]
- Lupski, J.R.; Liu, P.; Stankiewicz, P.; Carvalho, C.M.B.; Posey, J.E. Clinical genomics and contextualizing genome variation in the diagnostic laboratory. Expert Rev. Mol. Diagn. 2020, 20, 995–1002. [Google Scholar] [CrossRef] [PubMed]
- Coe, B.P.; Witherspoon, K.; Rosenfeld, J.A.; et al. Refining analyses of copy number variation identifies specific genes associated with developmental delay. Nat. Genet 2014, 46, 1063–1071. [Google Scholar] [CrossRef] [PubMed]
- Whitby, H.; Tsalenko, A.; Aston, E.; et al. Benign copy number changes in clinical cytogenetic diagnostics by array CGH. Cytogenet Genome Res. 2008, 123, 94–101. [Google Scholar] [CrossRef] [PubMed]
- Girirajan, S.; Brkanac, Z.; Coe, B.P.; et al. Relative burden of large CNVs on a range of neurodevelopmental phenotypes. PLoS Genet 2011, 7, e1002334. [Google Scholar] [CrossRef] [PubMed]
- Borlot, F.; Regan, B.M.; Bassett, A.S.; Stavropoulos, D.J.; Andrade, D.M. Prevalence of pathogenic copy number variation in adults with pediatric-onset epilepsy and intellectual disability. JAMA Neurol. 2017, 74, 1301–1311. [Google Scholar] [CrossRef] [PubMed]
- Cucinotta, F.; Lintas, C.; Tomaiuolo, P.; et al. Diagnostic yield and clinical impact of chromosomal microarray analysis in autism spectrum disorder. Mol. Genet Genom. Med. 2023, 11, e2182. [Google Scholar] [CrossRef] [PubMed]
- Riggs, E.R.; Andersen, E.F.; Cherry, A.M.; et al. Technical standards for the interpretation and reporting of constitutional copy-number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen). Genet Med. 2020, 22, 245–257. [Google Scholar] [CrossRef] [PubMed]
- Richards, S.; Aziz, N.; Bale, S.; et al. ACMG Laboratory Quality Assurance Committee. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015, 17, 405–424. [Google Scholar] [CrossRef] [PubMed]
- MacArthur, D.G.; Manolio, T.A.; Dimmock, D.P.; Rehm, H.L.; Shendure, J.; Abecasis, G.R. Guidelines for investigating causality of sequence variants in human disease. Nature 2014, 24, 469–476. [Google Scholar] [CrossRef] [PubMed]
- Landrum, M.J.; Lee, J.M.; Benson, M.; et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 2018, 46, D1062–D1067. Available online: https://www.ncbi.nlm.nih.gov/clinvar/ (accessed on June 22; 2026). [CrossRef] [PubMed]
- Zarrei, M.; MacDonald, J.R.; Merico, D.; Scherer, S.W. A copy number variation map of the human genome. Nat. Rev. Genet 2015, 16, 172–83. [Google Scholar] [CrossRef] [PubMed]
- Hap Map Consortium. Integrating common and rare genetic variation in diverse human populations. Nature 2010, 4, 51-58. See the replacement 1000 genomes website at http://www.1000genomes.org/; for updated DNA variant information; accessed June 22; 2026.
- Lek, M.; Karczewski, K.J.; Minikel, E.V. Exome Aggregation Consortium. Analysis of protein-coding genetic variation in 60;706 humans. Nature 2016, 536, 285–291. [Google Scholar] [CrossRef] [PubMed]
- Tonk, V.S.; Wilson, G.N.; Yatsenko, A.S.; et al. Familial duplication dup(1)(p36.3) with minimal dysmorphism. Am. J. Med. Genet 2005, 139A, 136–140. [Google Scholar] [PubMed]
- Tonk, V.; Kyhm, J.H.; Gibson, C.E.; Wilson, G.N. Interstitial deletion 5q14.3q21.3 with MEF2C haploinsufficiency and mild phenotype: when more is less. Am. J. Med. Genet 2011, 155A, 1437–1441. [Google Scholar] [CrossRef] [PubMed]
- DECIPHER; mapping the clinical genome. Accessed June 22; 2026; DECIPHER v11.38: Mapping the clinical genome.
- Database of Genomic Variants (***dgv***). Accessed June 22; 2026; Database of Genomic Variants [*** dgv ***].
- MedCalc Software Ltd.; accessed June 22; 2026; https://www.medcalc.org/calc.
- Brah, H.S.; Sran, N.; Sanghani, S.; et al. Clinical genetic testing in schizophrenia: A systematic review and meta-analysis. Biol. Psychiatry 2026, 99, 541–549. [Google Scholar] [CrossRef] [PubMed]
- Grünblatt, E.; Oneda, B.; Ekici, A.B.; et al. High resolution chromosomal microarray analysis in paediatric obsessive-compulsive disorder. BMC Med. Genom. 2017, 10, 68. [Google Scholar] [CrossRef] [PubMed]
- Asanad, K.; Greenfeld, E.; Scherer, S. W.; et al. Uncovering the association between complete AZFc microduplications and spermatogenic ability: The first reported series. Cureus 2023, 15, e51140. [Google Scholar] [CrossRef] [PubMed]
- Wilson, G.N.; Tonk, V.S. Autism: A different vision. Open J. Psych. 2018, 8, 263–296. [Google Scholar] [CrossRef]
- Jones, W.; Klaiman, C.; Richardson, S.; et al. Eye-tracking-based measurement of social visual engagement compared with expert clinical diagnosis of autism. JAMA 2023, 330, 854–865. [Google Scholar] [CrossRef] [PubMed]
- Wu, Q.; Morrow, E.M.; Gamsiz Uzun, E.D. A deep learning model for prediction of autism status using whole-exome sequencing data. PLoS Comput Biol. 2024, 20, e1012468. [Google Scholar] [CrossRef] [PubMed]
- de Faber, J.T.; Kingma-Wilschut, C. Amblyopia. Curr. Opin. Ophthalmol. 1996, 7, 8–12. [Google Scholar] [CrossRef] [PubMed]
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